Designing an ideal anticancer molecule

Hypotheses

  1. Since cancer cells are different from normal cells in many aspects, there exists a well-defined molecular mechanism differentiating cancer (immortal) cells from adult (differentiated, mortal) cells. We will call it Cancer-Specific Molecular Machinery (CSMM). By definition, CSMM is common for many (perhaps, all) types of cancer.

  2. CSMM is present not only in tumor cells and cancer cell lines, but also in cancer stem cells, and it different from the pluripotency machinery in “normal” stem cells.

  3. CSMM can be targeted by small molecule drugs. In other words, it is possible to find a small molecule that will be toxic for most/all cancer cells and much less toxic for normal cells.

  4. Among the >100,000 molecules NCI has already tested on the NCI-60 cell panel, some of the molecules are already targeting CSMM, albeit inefficiently.

  5. By bioinformatic analysis of NCI-60 datasets, it is possible to identify a group of molecules enriched with the CSMM-targeting molecules. We will call this group CSMM-targeting candidates.

  6. Based on the identified CSMM-targeting candidates and NCI-60 data, it is possible to build empirical models of CSMM-targeting molecules with sufficient predictive power for meaningful prediction of their Efficacy E, Unspecificity U and Safety S.

  7. Based on the above predictions for millions of molecules generated in silico based on the best CSMM-targeting candidates, it is possible to identify most promising candidates.

Aims

  1. To predict novel small molecule candidates which should be:
    • active (in terms of \(IC_{50}/LC_{50}\)),
    • unspecific (similar \(IC_{50}/LC_{50}\) across different cancer cell lines),
    • safe (non-toxic).

  2. Synthesize these candidate molecules and test their activity and unspecificity on cell panels, including the NCI-60 panel.

  3. Provided E and U are high, find the protein targets and mechanism(s) of action of these molecules using the FITExP method (expression-based analysis).

  4. Confirm the protein targets of these molecules using the SITExP method (solubility-based analysis).

  5. Based on these results, test the hypothesis 1.

  6. Determine the toxicity of the candidate molecules on normal stem cells, thus testing the hypothesis 2.

  7. Provided the targets and the mechanisms are novel and look like a plausible CSMM candidate, determine experimentally the safety S of the novel molecules, thus testing the hypotheses 3-7.

Methods

  1. “Seed” selection (ACh).

    1. DTP-NC60 dataset will be used as a starting point for candidate molecule identification. There are more than 100,000 small molecules tested, ~33,000 has measured IC50 values in at least 50 of 60 cell lines. For each of the compound in dataset we will calculate following characteristics:
      • Efficacy E, as \(-log(IC_{50})\) averaged over cell lines.
      • Unspecificty U, difference between the max and mean \(-log(IC_{50})\).
      • Safety S, using GUSAR’s Acute Mice Toxicity model.
    2. We will define the figure-of-merit function Q(E,U,S) assingns then highest value to the ”best” molecules.
    3. Then we will select 500-1000 best candidates with the highest Q values.

  2. Clustering by MOA (ACh).

    For each of the selected candidate molecules, an activity spectrum (AS) will be calculated using PASS software. Then the molecules will be clustered by similarity (correlation or covariation) of AS. One or two most consistent and large clusters will be selected (expected to comprise 20-50 molecules each).

  3. Cluster enrichment and candidate selection (ACh).

    1. Each of the selected clusters will be enriched by structurally similar molecules from the DTP-NC60 dataset.
    2. For each of the selected clusters, we will build, using PASS and GUSAR, models predicting E and U. Toxicity model already exists (GUSAR).
    3. For each cluster, we will select molecules from the Chembl database that pass the structural similarity threshold (will be defined for each cluster).
    4. For thus selected molecules E, U and S will be calculated, as well as Q.
    5. Best hits (max Q) will be selected in each cluster. Based on their structural features and AS, it will be analyzed whether they represent essentially the same structure or different structures. In the first case, simplest structure will be chosen as “seed”. In the latter case, several different simplest structures will be chosen as seeds.

  4. Experimental validation (AS).

    The seeds from each cluster will be ordered (or synthesized) and tested in the lab on at least three different cancer cell lines (HCT116, RKO and A375(?)). Experimental IC50 values will be determined. All hits found to be active will be sent to NCI-60 for testing on 60 cell lines.

  5. Targets and MOA identification (AS and ACh).

    FITExP and SITExP methods will be used to identify the targets and MOA of the verified hits.

  6. Novel target validation (AS).

    Novel target candidates identified by UTIExP will be validated using siRNA.

  7. Safety of novel molecules (AS; outsourced).

    Determine the toxicity of the candidate molecules on normal stem cells. Safety of novel molecules for animals will be tested by commercial labs.

1. Seed selection

Preparing environment

In [1]: 
# For inline graphics
%pylab inline
from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw
Draw.DrawingOptions.elemDict[0]=(0.,0.,0.)  # draw dummy atoms in black
from rdkit.Chem import PandasTools
from rdkit.Chem import AllChem as Chem
from rdkit.Chem import DataStructs

# Pandas and Numpy - musthave
import pandas as pd
import numpy as np
%config InlineBackend.figure_format='retina'
# Love this!
import mpld3
mpld3.enable_notebook()

from IPython.display import display
from IPython.display import display_pretty, display_html, HTML, Javascript, Image

pd.options.display.mpl_style = 'default'
pd.options.display.float_format = '{:.2f}'.format
rcParams['figure.figsize'] = 12,9
import warnings
warnings.filterwarnings('ignore')

HTML('''<script>
code_show=true; 
function code_toggle() {
 if (code_show){
 $('div.input').hide();
 } else {
 $('div.input').show();
 }
 code_show = !code_show
} 
$( document ).ready(code_toggle);
</script>
The raw code for this IPython notebook is by default hidden for easier reading.
To toggle on/off the raw code, click <a href="javascript:code_toggle()">here</a>.''')

Populating the interactive namespace from numpy and matplotlib
Out[1]:
The raw code for this IPython notebook is by default hidden for easier reading. To toggle on/off the raw code, click here.

Load NCI60 data (structures and activities)

In [2]: 
gi50 = pd.read_table('/Volumes/public/Users/Alexey/DrugDiscovery/NCI60/DTP_NCI60_RAW.txt', skiprows=7, sep='\t', na_values='-')
not_cells = [x for x in gi50.columns if ':' not in x]
cells = [x for x in gi50.columns if ':' in x]
smiles = pd.read_table('/Volumes/public/Users/Alexey/DrugDiscovery/NCI60/NCIOPENB_SMI', sep='\s+', header=None, index_col=0, names=['hz','smiles'])

print("{0} records from DTP_NCI60 were loaded. {1} structures were loaded from SMILES file".format(len(gi50.index), len(smiles)))

73841 records from DTP_NCI60 were loaded. 237771 structures were loaded from SMILES file

Averaging

Loaded data from DTP_NCI60 may contain multiple records for single compounds. Thus, we will take median GI50 value for each compound in each cell line

In [3]: 
data_melted = pd.melt(gi50, id_vars=not_cells)
data_pivot = pd.pivot_table(data_melted, values='value', index='NSC #',columns='variable', aggfunc=np.median)
print("Data for {0} compounds was loaded".format(len(data_pivot)))

Data for 49847 compounds was loaded
In [4]: 
HTML(data_pivot.iloc[:5,:10].to_html())
Out[4]:
variable BR:BT_549 BR:HS578T BR:MCF7 BR:MDA_MB_231 BR:T47D CNS:SF_268 CNS:SF_295 CNS:SF_539 CNS:SNB_19 CNS:SNB_75
NSC #
1 4.81 4.75 4.83 4.79 5.60 4.78 4.63 4.77 4.05 4.94
17 6.47 4.60 4.73 4.51 6.37 5.75 5.73 6.11 4.00 4.97
26 nan nan 4.97 5.36 4.85 5.36 5.70 5.44 4.84 5.77
89 nan nan nan nan nan 4.00 4.00 4.00 4.00 4.00
171 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00 4.00

Filtering for sufficient number of measurements

We will keep only compounds with GI50 values in at least 40 of 60 cell lines

In [5]: 
nans = data_pivot.apply(lambda x: sum(isnan(x)), axis=1)
gi50_ok = data_pivot[nans<20]
print("{0} compounds left for further analysis".format(len(gi50_ok)))

48758 compounds left for further analysis

GI50 distribution properties for each compound

In [6]: 
from scipy import stats
gi50_ok['NSC #'] = gi50_ok.index
data_melted = pd.melt(gi50_ok, id_vars='NSC #')
grouped = data_melted.groupby('NSC #')
def skew(x):
    return stats.skew(x.dropna(), bias=True)
def kurtosis(x):
    return stats.skew(x.dropna(), bias=True)

data_averaged = grouped['value'].agg({
    'mean': lambda x: mean(x.dropna()),
    'median': lambda x: median(x.dropna()),
    'min': lambda x: np.min(x.dropna()),
    'max': lambda x: np.max(x.dropna()),
    'skew': lambda x: stats.skew(x.dropna(), bias=True),
    'sd' : lambda x: np.std(x.dropna()),
    'dif_from_median' : lambda x: sum(abs(x.dropna()-median(x.dropna()))>0.001),
    'kurtosis': lambda x: stats.kurtosis(x.dropna(), fisher=True, bias=True)})
data_averaged['cv'] = data_averaged['sd'] / data_averaged['mean']
HTML(data_averaged.head().to_html())
Out[6]:
min kurtosis max skew sd median dif_from_median mean cv
NSC #
1 4.05 0.08 5.70 0.82 0.35 4.79 58.00 4.89 0.07
17 4.00 -0.96 7.30 0.64 1.00 4.73 58.00 4.93 0.20
26 4.83 -1.40 5.78 -0.16 0.32 5.38 52.00 5.32 0.06
89 4.00 2.40 5.82 1.25 0.38 4.33 50.00 4.34 0.09
171 4.00 -3.00 4.00 0.00 0.00 4.00 0.00 4.00 0.00

Further data filtering

We will require at least 20 values over 60 cell lines to be different from median value (If many values are equal to median value it usually means only one concentration was measured).

In [7]: 
data_diff = data_averaged[(data_averaged['dif_from_median']>20) & (data_averaged['cv'] < 1.0) & (data_averaged['cv']>0)]
print("{0} compounds left for further analysis".format(len(data_diff)))

27168 compounds left for further analysis

Dataset overview in terms of GI50 values distribution

We have to subset our dataset in terms of - unspecificty U, - efficacy E.

To assess unspecificity of compounds, we will consider CV (standard deviation divided my the mean value):

In [8]: 
#matplotlib.rc('text', usetex=False)
#matplotlib.rcParams['text.latex.preamble']=[r"\usepackage{amsmath}"]
density = stats.gaussian_kde(data_diff['cv'])
xx = np.linspace(0, 0.2, 300)
plot(xx, density(xx), lw=2)
fill_between(xx, density(xx),0, alpha=0.2)
xlim([0.,0.3])
data_diff['cv'].hist(bins=200, normed=True)
xlabel(r'CV')
Out[8]:
<matplotlib.text.Text at 0x1197d8bd0>

To assess efficacy E we will consider -log(GI50) values distribution:

In [10]: 
density = stats.gaussian_kde(data_diff['mean'])
xx = np.linspace(data_diff['mean'].min(), data_diff['mean'].max(), 300)
plot(xx, density(xx), lw=2)
fill_between(xx, density(xx),0, alpha=0.2)
data_diff['mean'].hist(bins=50, normed=True)
xlabel('Mean -log10(GI50)')
Out[10]:
<matplotlib.text.Text at 0x119aa69d0>

And scatterplot - CV vs mean -log10(GI50) (some points omitted):

In [12]: 
data_5 = data_diff.iloc[::15,:]
scatter(data_5['mean'], data_5['cv'])
xlabel('Mean -log10(GI50)')
ylabel('CV')
Out[12]:
<matplotlib.text.Text at 0x11a9e0410>

Shortlist generation

Instead of figure of merit function S i would suggest to use figure of merit rules:

  • high efficacy – \(mean(-log10(GI_{50}) > 6\);
  • low specificity – \(CV(-log10(GI_{50}) < 5\%\);
  • toxicity will be calculated later.
In [29]: 
data_seeds = data_diff[(data_diff['mean']>6) & (data_diff['cv'] < 0.05)]
print('{0} compounds selected'.format(len(data_seeds)))

512 compounds selected
In [31]: 
suppl = Chem.SDMolSupplier('/Users/black/Google Drive/NCI60-drugs/March2012_2d_dos.sdf')
compounds = {}
for mol in suppl:
    if mol:
        nnsc = int(mol.GetProp('NSC'))
        compounds[nnsc] = mol
In [47]: 
data_seeds = data_diff[(data_diff['mean']>6) & (data_diff['cv'] < 0.05)]
print('{0} compounds selected'.format(len(data_seeds)))
data_seeds['Mol'] = [(x in compounds) and compounds[x] or '' for x in data_seeds.index]
data_seeds = data_seeds[data_seeds.Mol != '']
print('For {0} compounds molecular structure found'.format(len(data_seeds)))
#PandasTools.AddMoleculeColumnToFrame(data_seeds, smilesCol='smiles', molCol='Mol')
HTML(data_seeds.sort('mean', ascending=False).head().to_html())

512 compounds selected
For 450 compounds molecular structure found
Out[47]:
min kurtosis max skew sd median dif_from_median mean cv Mol
NSC #
670038 10.00 -0.18 11.47 0.23 0.35 10.61 56.00 10.63 0.03 Mol
693565 9.26 1.99 10.60 -1.36 0.30 10.35 60.00 10.33 0.03 Mol
357704 9.42 -0.32 10.73 -0.21 0.27 10.07 60.00 10.02 0.03 Mol
707389 8.34 1.33 10.05 -1.15 0.38 9.60 58.00 9.57 0.04 Mol
611747 7.00 17.43 9.94 -3.73 0.44 9.73 56.00 9.56 0.05 Mol
In [39]: 
pass_input = '/Volumes/public/Users/Alexey/DrugDiscovery/NCI60/20141219_magicbullet_forpass.sdf'
writer = Chem.SDWriter(pass_input)
for idx,row in data_seeds.sort('mean', ascending=False).iterrows():
    mol = row['Mol']
    mol.SetProp('gi50_mean',"%.4f"%row['mean'])
    mol.SetProp('gi50_cv',"%.4f"%row['cv'])
    mol.SetProp('gi50_max',"%.4f"%row['max'])
    mol.SetProp('gi50_median',"%.4f"%row['median'])
    writer.write(mol)
writer.close()
In [45]: 
pass_output = pass_input.replace('.sdf', ' (PASS2A).CSV')
pass_result = pd.read_csv(pass_output, skiprows=8, index_col=0)
In [46]: 
print("For {0} molecules PASS predictions were obtained".format(len(pass_result)))

For 385 molecules PASS predictions were obtained
In [48]: 
effects = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-1-E  Effects.txt").readlines()]
mechanisms = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-2-M  Mechanisms.txt").readlines()]
toxicity = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-4-T  Toxicity.txt").readlines()]
metabolism = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-16-Z Metabolism.txt").readlines()]
transport = [a.strip() for a in open("/Users/black/Dropbox/projects/Best Anticancer Drug/PASS_categories/2A-64-C Transport.txt").readlines()]

pass_toxic = pass_result[[a for a in toxicity if 'Toxic' in a or 'toxic' in a]]
In [81]: 
from sklearn import decomposition, preprocessing
pass_mechanisms = pass_result[mechanisms]
pass_mechanisms_scaled = preprocessing.scale(pass_mechanisms)
pca = decomposition.PCA()
pca.fit(pass_mechanisms_scaled)
Out[81]:
PCA(copy=True, n_components=None, whiten=False)
In [82]: 
X = pca.transform(pass_mechanisms)

MOA Clustering

Selected compounds were subjected for PCA analysis. Each compound was characterised by a vector of PASS activities (Mechanisms section) with at least 20 non-negative values over all selected compounds.

Summary of PCA analysis:

  • PC1 explained 44.1% of variance;
  • PC2 explained 11.6% of variance;
  • 25 PCs explained 90% of variance;
  • 49 PCs explaned 95% of variance.

Results of PCA analysis were subjected to agglomerative hierarchical clustering procedure. 8 clusters were generated.

In [89]: 
Image('PCAclusters.png', width=600)
Out[89]:
In [94]: 
clusters = pd.read_csv('clusters2/clustered.csv', index_col=0)
clusters_grouped = clusters.groupby('clust')
In [163]: 
htmlall = ''
nsc_info = gi50[[u'Drug name', u'FDA Status', u'Mechanism of Action']]
nsc_info.index = gi50[u'NSC #']
nsc_info.drop_duplicates(inplace=True)
nsc_info.fillna('', inplace=True)
for num, dd in clusters_grouped.groups.items():
    clusterdata_1 = data_seeds.ix[dd,['median','cv','min','max','Mol']]
    clusterdata_1 = pd.merge(clusterdata_1, pass_toxic[['Cytotoxic','Embryotoxic']], left_index=True, right_index=True, how='left')
    clusterdata_1 = pd.merge(clusterdata_1, nsc_info, left_index=True, right_index=True)
    htmlall += "<h3>Cluster {0}</h3>".format(num)+clusterdata_1.sort('median', ascending=False).to_html() + "<br/>"
In [164]: 
HTML(htmlall)
Out[164]:

Cluster 1

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
611747 9.73 0.05 7.00 9.94 Mol 3.11 -2.02 Calyculin A
671677 8.30 0.03 7.51 8.30 Mol 11.39 -0.70 Sphinxolide B
702924 8.20 0.04 7.60 9.28 Mol 12.34 -1.04 sphinxolide F
671678 7.40 0.04 6.46 8.23 Mol 11.16 -0.84 Sphinxolide C Unknown
702923 7.27 0.05 6.39 8.15 Mol 8.62 -0.69 sphinxolide E
671680 6.93 0.04 6.43 7.84 Mol 11.07 -0.86 Sphinxolide Unknown
722656 6.53 0.02 6.22 6.86 Mol 4.58 -0.03 Partricin A morpholide

Cluster 2

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
665803 8.65 0.05 6.96 9.00 Mol 2.74 -2.53 15H-Pyrrolo[2,1-f][1,15,4,7,10,20] dioxatetraazacyclotricosine-1,4,8,13,16,18,21-heptaone, docosahydro-11-hydroxy-3-[(4-methoxyphenyl)methyl]- 2,6,17-trimethyl-15-(methylethyl)-10-(1-methylpropyl)- 2
712199 8.42 0.03 7.11 8.60 Mol 3.15 -2.72 Didemnin B aminomethylene
714370 8.33 0.05 6.65 9.00 Mol 2.22 -2.65 dehydrotamandarin-A
682345 7.75 0.03 6.50 7.96 Mol 0.15 -2.87 Aurantimycin B Unknown

Cluster 3

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
357704 10.07 0.03 9.42 10.73 Mol 2.06 -0.15 5,12-Naphthacenedione, 10-[[3-(3-cyano-4-morpholinyl)-2,3,6-trideoxy-.alpha.- L-lyxo-hexopyranosyl]oxy]-7,8,9,10-tetrahydro-6,8,11- trihydroxy-8-(hydroxyacetyl)-1-methoxy-, (8S-cis)- Db
641318 9.31 0.05 7.32 10.00 Mol 2.25 0.76 5,12-Naphthacenedione, 10-[[3-[[4,4-di(acetyloxy)butyl]amino]- 2,3,6-trideoxy-.alpha.-L-lyxohexopyranosyl]oxy]- 7,8,9,10-tetrahydro-6,8,11-trihydroxy- 8-(hydroxyacetyl)-1-methoxy-, hydrochloride
70929 9.20 0.05 8.60 10.50 Mol 1.42 -1.28 Antibiotic B26,158 Unknown
609394 9.08 0.05 8.00 9.83 Mol 5.24 -0.70 B7722121F049(=K053)
603724 8.75 0.02 7.93 9.00 Mol 7.59 -0.36 Roritoxin B from m. roridum
641319 8.66 0.03 8.25 9.47 Mol 2.25 0.75 5,12-Naphthacenedione, 10-[[3-[[5,5-di(acetyloxy)pentyl]amino]- 2,3,6-trideoxy-.alpha.-L-lyxohexopyranosyl]oxy]- 7,8,9,10-tetrahydro-6,8,11-trihydroxy- 8-(hydroxyacetyl)-1-methoxy-, hydrochloride
21205 8.39 0.02 7.82 8.43 Mol 1.36 -1.14 Pluramycin A Unknown
114781 8.28 0.03 6.89 8.89 Mol 4.84 -1.07 Pederin
328167 8.25 0.03 7.21 8.30 Mol 4.90 -0.59 RORIDIN A, HYDROXY-, 8B-
243023 8.12 0.03 7.78 9.43 Mol 2.23 0.41 Cinerubin B hydrochloride
670121 8.12 0.03 7.53 8.79 Mol 1.71 1.04 11-Hydroxy aclacinomycin A
670122 8.06 0.04 6.52 8.98 Mol 1.50 0.46 11-Hydroxy aclacinomycin X
639655 8.05 0.05 7.44 9.00 Mol 1.78 -0.34 3'-Deamino-3'-(4-morpholinyl)-13-dihydro-adriamycin hydrocholoride dihydrate Unknown
269146 8.00 0.05 6.23 8.00 Mol 1.33 2.05 Antibiotic 6604-9A
261045 7.92 0.04 7.00 8.00 Mol 2.28 0.80 N,N-Dimethyladriamycin Unknown
269754 7.76 0.04 6.31 9.00 Mol 5.38 -0.49 BACCHARIS PRINCIPLE B-2 (B800157F248 AND K381)
267469 7.62 0.05 5.54 8.18 Mol 2.22 0.72 Esorubicin T2
136044 7.49 0.03 6.84 7.88 Mol 1.63 0.26 Rhodomycin A
750154 7.43 0.03 6.78 8.04 Mol 2.74 -1.12 salarin C
267229 7.34 0.05 6.50 7.76 Mol 1.59 0.54 Pyrromycin
268239 7.29 0.04 6.52 7.83 Mol 2.28 0.70 5,12-Naphthacenedione, 7,8,9,10-tetrahydro-6,8,11-trihydroxy-8-(hydroxyacetyl)-1-methoxy-10-[[2,3,6-trideoxy-3-(diethylamino)-.alpha.-L-lyxo-hexopyranosyl]oxy]-, hydrochloride, (8S-cis)- Unknown
159628 6.68 0.05 6.06 7.49 Mol 0.26 -0.85 (8,8'-Bi-1H-naphtho[2,3-c]pyran)-3,3'-diacetic acid, 3,3',4,4'-tetrahydro-9,9',10,10'-tetrahydroxy-7,7'-dimethoxy-1,1'-dioxo-, dimethyl ester
102815 6.50 0.04 5.68 7.15 Mol 0.89 -0.20 Compound D from Nogalamycin
42076 6.44 0.04 5.34 6.65 Mol 1.71 0.13 .beta.-D-Glucopyranoside, 5,5a,6,8,8a,9-hexahydro-6-oxo-5-(3,4,5-trimethoxyphenyl)furo[3',4':6,7]naphtho[2,3-d]-1,3-dioxol-9-yl, [5R-(5.alpha.,5a.beta.,8a.alpha.,9.alpha.)]-
708496 6.40 0.03 5.86 7.29 Mol 0.32 -0.90 1-O-(3-O-.beta.-D-glucopyranosylbutyryl)pancratistatin
663567 6.38 0.05 5.37 6.73 Mol 0.72 3.54 15-tert-butyl-20-deoxyvinblastine Unknown
626171 6.09 0.04 5.56 6.95 Mol 5.17 -1.24 7,17,18-Trimethoxy mycalamide A
702208 6.03 0.04 5.29 6.62 Mol 1.49 -0.35 Heliquinomycin
693702 6.00 0.05 5.52 6.69 Mol 2.10 -1.24 Gambogic acid

Cluster 4

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
291312 8.86 0.05 6.87 9.00 Mol 4.01 -0.34 VERRUCARIN A, 8-HYDROXY Unknown
707148 8.27 0.04 7.10 8.60 Mol 1.75 0.78 Odoroside H
138780 8.10 0.02 7.69 8.34 Mol 2.39 2.17 Fusariotoxin T 2
25485 8.00 0.03 6.89 8.00 Mol 1.76 0.95 g-Strophanthin
266494 8.00 0.04 6.77 8.00 Mol 0.95 -0.54 Simalikalactone D
163062 7.95 0.04 6.99 8.59 Mol 1.02 -0.22 Triptolid Unknown
727038 7.88 0.03 6.95 8.00 Mol -0.36 -0.86 CDDO-Im
177378 7.78 0.02 7.26 8.00 Mol 2.17 2.13 Anguidine
650471 7.78 0.04 7.18 8.30 Mol 2.22 0.29 Calotropin
688285 7.75 0.04 6.66 8.00 Mol 2.24 0.10 7,8-Dehydrocalotropin Unknown
751641 7.72 0.03 6.89 8.00 Mol 0.75 -0.61 Triptolide 14-tert-butyl carbonate, tert-Butyl (3bS,4aS,5aR,6R,6aS,7aS,7bS,8aS,8bS)-6a-iso-propyl-8b-methyl-1-oxo-1,3,3b,4,4a,6,6a,7a,7b,8b,9,10-dodecahydrotrisoxireno[4b,5:6,7:8a,9]phenanthro[1,2-c]
179180 7.70 0.02 7.22 8.00 Mol 0.57 0.41 Norcassamide, hydrochloride
278571 7.69 0.04 6.82 8.00 Mol 2.47 2.10 Ht-2 toxin
751642 7.66 0.04 6.54 8.00 Mol 0.81 -0.37 Triptolide N,N-dimethylacetate, (3bS,4aS,5aR,6R,6aS,7aS,7bS,8aS,8bS)-6a-isopropyl-8b-methyl-1-oxo-1,3,3b,4,4a,6,6a,7a,7b,8b,9,10-dodecahydrotrisoxireno[4b,5:6,7:8a,9]phenanthro[1,2-c]furan-6-yl N,N-d
93134 7.62 0.03 7.43 8.23 Mol 2.26 0.26 Bufa-20,22-dienolide, 3-[(6-deoxy-4-O-.beta.-D-glucopyranosyl-.alpha.-L-mannopyranosyl)oxy]-5,14-dihydroxy-19-oxo-, (3.beta.,5.beta.)- (9CI)
747712 7.61 0.03 6.65 8.00 Mol 0.57 -0.69 18-benzoyloxy-19-benzoylfuranotriptolide
7529 7.60 0.03 6.77 8.00 Mol 1.72 0.97 Digitoxin
143925 7.57 0.04 6.65 7.87 Mol 1.78 0.73 Calotropin (6CI, 7CI, 8CI) Unknown
238181 7.56 0.04 6.04 7.95 Mol 0.66 -0.54 Isobrucein B
713200 7.54 0.04 6.73 8.00 Mol 0.08 -0.27 Bardoxolone Methyl
106399 7.48 0.05 6.02 7.78 Mol 3.14 -0.46 .alpha.-Elaterin
7534 7.43 0.03 7.01 8.25 Mol 1.56 0.11 SCILLIROSIDIN, GLYCOSIDE
95100 7.38 0.04 6.69 7.73 Mol 1.70 1.17 Digoxin FDA approved
7533 7.33 0.05 6.43 7.86 Mol 2.31 1.56 Allocor
135036 7.30 0.03 7.13 8.45 Mol 1.39 0.14 SCILLIGLAUCOSIDIN
117180 7.27 0.03 6.82 7.60 Mol 1.92 0.08 Scillirosidin, 1.alpha.,2.alpha.-epoxy-
114340 7.14 0.05 6.36 7.81 Mol 1.13 -0.02 Cochliobolin A
112167 6.77 0.02 6.22 7.00 Mol 2.76 -0.57 Cucurbitacine (i)
135077 6.69 0.05 6.24 7.50 Mol 1.39 -0.78 BERSALDEGENIN 1,3,5-ORTHOACETATE
682561 6.57 0.05 6.03 7.21 Mol 1.73 0.51 Cardenolide 2 Unknown
94743 6.52 0.04 6.00 7.42 Mol 2.59 -0.29 Cucurbitacin A
179176 6.49 0.04 5.75 6.78 Mol 0.54 0.03 1-Phenanthrenecarboxylic acid, tetradecahydro-2,9-dihydroxy-1,4a,8-trimethyl-7-[2-[2-(methylamino)ethoxy]-2-oxoethylidene]-10-oxo-, methyl ester, hydrochloride, [1R-(1.alpha.,2.alpha.,4a.alpha.,4b.be
135073 6.42 0.04 5.92 6.78 Mol 2.12 -0.08 WITHACNISTIN
714608 6.22 0.03 5.45 6.40 Mol 2.18 1.30 Weltonin

Cluster 5

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
670038 10.61 0.03 10.00 11.47 Mol 6.26 -1.47 Cryptophycin B Unknown
348115 8.99 0.03 8.64 10.00 Mol 1.10 -0.32 Gilvocarcin V
648910 8.67 0.03 8.43 9.67 Mol 0.15 -0.51 Hydramycin
52947 8.50 0.04 7.87 9.00 Mol -0.04 -0.95 A 80856F30
681239 8.48 0.03 7.72 8.83 Mol -0.82 -1.91 Bortezomib FDA approved Pr
646616 8.44 0.04 7.94 9.72 Mol 0.15 -1.06 MDP-C857
355461 8.40 0.03 7.88 8.96 Mol 1.47 -0.69 B621099K443 Unknown
693546 8.34 0.05 7.80 9.91 Mol 0.37 -1.25 1H-Benz[e]indol-5-amine, 1-(chloromethyl)-2,3-dihydro-N-methyl- 3-[(5,6,7-trimethoxy-1H-indol-2-yl)carbonyl]-
326408 8.31 0.04 6.57 8.61 Mol -0.04 -1.03 Rocaglamide Unknown
670655 8.30 0.04 6.97 8.65 Mol -0.26 -1.32 4a,14a-Epoxy-4,14-[3]hexene[1,5]diynonaphtho[2,3-c] phenanthridine-7,12-dione, 1,2,3,4,13,14-hexahydro- 4,6-dihydroxy-3,3-dimethoxy-1-methyl-, stereoisomer
45383 8.00 0.03 6.89 8.32 Mol -0.05 0.82 A 050165L302
651849 8.00 0.03 6.76 8.28 Mol 0.08 -0.88 .alpha.-D-Glucopyranoside, phenylmethyl 2-acetylamino- 2-deoxy-3-O-[3-[5-[3-(9,10-dihydro-4-nitroacridin- 10-ylamino)propoxy]-1-amino-1,5-dioxo-2-pentylamino]- 3-(3-oxo-2-propylamino)-3-oxo-2-propyl]-
83950 8.00 0.03 8.00 8.89 Mol -0.05 0.82 Streptonigrin Unknown
382459 8.00 0.05 6.52 8.00 Mol 0.00 -0.92 1H-Indole-4,7-dione, 5-(1-aziridinyl)-3-(hydroxymethyl)-2-(3-hydroxy-1-propenyl)-1-methyl- Unknown
400979 7.99 0.05 5.94 8.66 Mol 0.39 -0.49 DR-15978 Unknown
32743 7.92 0.03 7.06 8.38 Mol 0.61 0.98 Acetoxycycloheximide
648060 7.89 0.03 7.01 8.00 Mol 0.52 -0.54 Viridenomycin Unknown
693540 7.87 0.02 7.51 8.00 Mol 0.20 -1.17 Acetamide, N-[2-[[5-amino-1-(chloromethyl)-1,2-dihydro- 3H-benz[e]indol-3-yl]carbonyl]-1H-indol-5-yl]-
216128 7.85 0.04 6.88 8.00 Mol 2.19 -0.60 Borrelidin
123111 7.81 0.05 6.77 8.00 Mol 0.61 -0.97 Azirino[2',3':3,4]pyrrolo[1,2-a]indole-4,7-dione, 1,1a,2,8b-tetrahydro-8-(hydroxymethyl)-6-methoxy-1,5-dimethyl-, carbamate (ester)
400978 7.78 0.04 6.61 8.42 Mol 0.16 -0.51 DR-15977 Unknown
56310 7.74 0.03 7.11 8.00 Mol 1.84 0.18 Antibiotic from Penicillium cyaneum Unknown
712399 7.73 0.05 6.48 8.30 Mol 0.34 0.28 Ambewelamide A
713205 7.63 0.02 7.23 8.00 Mol -0.47 -0.90 Halofuginone Hydrobromide
106408 7.62 0.03 6.68 8.00 Mol -0.23 -1.31 Anthramycin methyl ether
381837 7.56 0.03 6.97 7.90 Mol -0.07 -0.59 trans-Dihydronarciclasine Unknown
708495 7.48 0.05 5.89 7.93 Mol -0.08 -0.96 Pancratistatin,1-O-(4-hydroxy-2-oxopentyl)-
692303 7.47 0.04 6.70 8.00 Mol 1.39 -0.24 2,3-Dihydro-3(R)-[4'hydroxyphenylsulfinyl]brefeldin A
89671 7.42 0.04 6.70 8.00 Mol 1.84 0.18 (+)-Brefeldin A
39147 7.42 0.04 6.63 8.00 Mol 0.42 0.75 Glutarimide, 3-[2-hydroxy-2-(5-hydroxy-3,5-dimethyl-2-oxocyclohexyl)ethyl]-,(-)- (8CI) Unknown
681229 7.36 0.05 6.28 7.88 Mol -0.60 -1.54 Boronic acid, [1-[[2-amino-3-(1-naphthalenyl)- 1-oxopropyl]amino]-3-methylbutyl]-, L-(S)-, hydrochloride
692306 7.32 0.05 6.68 8.00 Mol 1.17 -0.36 2,3-Dihydro-1,2-syn-2-[2'-aminopropylsulfenyl]-brefeldin A
349156 7.29 0.03 6.70 7.65 Mol -0.22 -0.71 Pancratistatin
745363 7.25 0.04 6.28 7.89 Mol -0.75 -1.35 Chaetocin from Chaetomium minutum
613009 7.17 0.04 6.24 7.65 Mol 1.21 -1.37 Jaspamide
682506 7.12 0.05 6.52 7.90 Mol 0.28 -1.18 Methanone, 3-(chloromethyl)-2,3-dihydro-6-(dimethylamino)- 1H-indol-1-yl-5,6,7-trimethoxy-1H-indol-2-yl- Unknown
697539 7.07 0.05 6.53 8.00 Mol 0.01 -1.56 6-Amino-3-chloromethyl-1-((5-(((benzofuran-2-yl)-carbonyl)amino)indol-2-ylcarbonyl)indoline
65380 6.86 0.04 6.45 7.50 Mol 0.27 -0.44 Anthrone, 4a.alpha.,9a.alpha.-epoxy-3.beta.-(2,3-epoxybutyryl)-1,2,3,4,4a,9a.alpha.-hexahydro-1.alpha.,3,4.alpha.,10.alpha.-tetrahydroxy-5-methoxy-2.beta.-methyl- (8CI) Unknown
99182 6.84 0.02 6.63 7.28 Mol -0.40 2.23 TRIBUTYLTIN STEARATE
117175 6.83 0.01 6.67 7.11 Mol -0.65 2.04 TRIBUTYLTIN 2,4-DICHLOROBENZOATE
99171 6.82 0.01 6.64 7.15 Mol -0.29 2.30 TRIBUTYLTIN UNDECYLENATE
99154 6.80 0.01 6.61 7.21 Mol -0.42 2.32 TRIBUTYLTIN PROPIONATE
325014 6.71 0.04 5.44 7.13 Mol 0.29 -0.10 Bactobolin
269142 6.64 0.03 5.63 6.98 Mol 2.18 1.98 ANGUIDINE DERIV SCIRPENTRIOL
718798 6.63 0.02 6.47 7.39 Mol 0.42 -0.47 Mensacarcin
138425 6.54 0.04 5.97 7.27 Mol 0.87 -0.35 Kinamycin C
267033 6.50 0.03 5.70 7.17 Mol 2.02 1.36 Trichothec-9-en-4-ol, 12,13-epoxy-, acetate, (4.beta.)- (9CI)
73846 6.49 0.03 5.70 6.81 Mol 2.02 1.36 Trichodermin
52141 6.47 0.05 5.66 7.14 Mol 2.20 -0.17 A 4426 Unknown
670851 6.46 0.04 5.91 7.13 Mol -0.43 -1.40 Manzamine A Unknown
667931 6.30 0.05 5.27 7.09 Mol -0.23 -1.11 6H-1,3-Dioxolo[4,5-g][1]benzopyran-6-amine, 7,8-dihydro- N-(4-methoxyphenyl)-8-(3,4,5-trimethoxyphenyl)-7-methyl- Unknown
354843 6.30 0.05 5.88 7.34 Mol 1.37 -0.24 Albacarcin M
17257 6.25 0.05 5.39 7.11 Mol 0.01 0.12 Acti-dione benzoylacetate
650718 6.21 0.05 5.61 6.75 Mol -0.58 -1.29 Roseophilin, HCl salt
676676 6.14 0.04 5.77 7.15 Mol 0.11 -0.56 ARQ monoacetate
730564 6.09 0.04 5.32 6.93 Mol 1.23 -0.44 Miliusane B
730563 6.08 0.05 5.64 6.77 Mol 1.21 -0.45 Miliusane A
746149 6.07 0.05 5.48 6.68 Mol -0.56 -1.14 N,N'-bis(4-bromo-2-fluorobenzoyl)-L-selenocystine bis(4-methoxyphenacyl) ester hemihydrate
626371 6.00 0.03 6.00 6.69 Mol 0.36 -0.56 Dehydroilludin M Unknown
744469 6.00 0.05 5.43 6.72 Mol -1.13 -1.56 3-cyano-3,3-diphenylpropyl 4-(3-[(11aS)-7-methoxy-5-oxo-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-8-yl]oxypropyl)-1-piperazinecarbodithioate
645318 5.91 0.05 5.72 6.74 Mol -0.31 -0.71 Benzyloxysanguinarine

Cluster 6

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
133114 8.17 0.03 7.62 9.00 Mol 0.61 -0.57 Adenosine, 5'-O-(aminosulfonyl)-
352890 8.03 0.03 7.34 8.90 Mol 0.63 -0.61 9-Deazaadenosine Unknown
675865 7.84 0.04 7.02 8.00 Mol 0.54 -0.65 Isothiazolo[4,5-d]pyrimidin-7-amine,3-(.beta.-D-ribofuranosyl)-
99843 7.74 0.04 6.63 8.00 Mol 0.78 -0.69 Antibiotic E 212 Unknown
188491 7.66 0.04 6.63 8.00 Mol 0.43 -0.20 7H-Pyrrolo[2,3-d]pyrimidine-5-carboxamide, 4-amino-6-hydrazino-7-.beta.-D-ribofuranosyl-
750854 7.61 0.03 7.19 8.00 Mol 0.36 -0.73 9H-Purine, 9-[5-O-(aminosulfonyl)-.beta.-D-ribofuranosyl)]-[(2R,3S,4R,5R)-3,4-Dihydroxy-5-(9H-purin-9-yl)tetrahydrofuran-2-yl]methyl sulfamate
143648 7.44 0.05 7.15 8.66 Mol 0.90 -0.61 Sangivamycin Hydrochloride
175630 7.26 0.04 6.62 7.76 Mol 0.59 -0.65 Toyocamycin, 6-amino-
65346 7.06 0.02 6.75 7.55 Mol 0.90 -0.61 Antibiotic from Streptomyces
664236 6.81 0.04 6.37 7.76 Mol 0.56 -0.62 Pyrrolo[2,1-f][1,2,4]triazine-4-amine, 7-.beta.-D-ribofuranosyl- Unknown
122816 6.77 0.03 6.48 7.53 Mol 0.91 -0.31 7H-Pyrrolo[2,3-d]pyrimidin-4(3H)-one, 7-.beta.-D-ribofuranosyl-, oxime
105827 6.73 0.04 6.22 7.71 Mol 0.81 -0.34 SANGIVAMYCIN,-THIO
359079 6.66 0.03 6.24 7.33 Mol 0.83 -0.68 Rebeccamycin
180525 6.59 0.04 6.02 7.25 Mol 0.67 -0.22 Sangivamycin, 6-aminothio-
116282 6.48 0.03 6.04 7.05 Mol 0.62 -0.98 7H-Pyrrolo[2,3-d]pyrimidine-5-carbohydroximic acid, 4-amino-7-.beta.-D-ribofuranosyl-, monohydrochloride (8CI)
72961 6.42 0.04 5.81 7.30 Mol 1.32 -0.36 3H-v-Triazolo[4,5-d]pyrimidine, 7-amino-3-.beta.-D-ribofuranosyl- (8CI) Unknown
367413 6.36 0.04 5.54 6.72 Mol 0.78 -0.65 1H-Pyrazolo[3,4-d]pyrimidine-3-carboximidamide, 4,5-dihydro-4-oxo-1-.beta.-D-ribofuranosyl-, monohydrochloride
102816 6.03 0.05 5.10 6.60 Mol 1.12 0.55 Azacitidine FDA approved DNMT
65423 5.93 0.04 5.61 6.51 Mol 0.89 -0.35 Isopurine, ribosyl- Unknown

Cluster 7

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
618487 8.00 0.04 7.18 9.22 Mol 0.44 -1.33 Staurosporine
638850 7.55 0.05 6.54 8.17 Mol 0.53 -1.24 7-Hydroxystaurosporine Clinical trial STK

Cluster 8

median cv min max Mol Cytotoxic Embryotoxic Drug name FDA Status Mechanism of Action
NSC #
650395 8.51 0.03 7.71 9.02 Mol -0.11 -0.65 Tyloindicine H Unknown
247561 8.50 0.04 7.80 9.00 Mol -0.29 -0.82 C 283
650396 8.34 0.02 7.68 8.76 Mol -0.26 -0.95 Tyloindicine I
645806 8.32 0.04 6.89 8.97 Mol -0.18 -0.70 9-Acridineamine, N-[2-[bis(2-hydroxyethyl)amino]ethyl]- 1-nitro-, dihydrochloride
645804 8.31 0.04 8.00 9.33 Mol -0.31 -0.82 9-Acridineamine, N-[5-(dimethylamino)pentyl]- 1-nitro-, dihydrochloride Unknown
645805 8.22 0.04 7.80 9.35 Mol -0.35 -0.83 1,3-Propanediamine, N-methyl-N'-(1-nitro-9-acridinyl)-,dihydrochloride Unknown
673792 8.03 0.04 6.32 8.66 Mol -0.15 -0.84 9-Acridinamine, N-[2-[(2-hydroxyethyl)amino]ethyl]-1-nitro-
711948 8.00 0.04 6.17 8.00 Mol 0.20 -0.87 Acetamide, N,N'-[1,8-dioxo-1,8-octanediyldi[1-(chloromethyl)- 2,3-dihydro-5-hydroxy-1H-benz[e]indole-3,7-diyl]]bis-
295505 8.00 0.02 7.20 8.00 Mol -0.33 -0.91 C 829
47147 8.00 0.04 6.60 8.00 Mol -0.65 -1.28 Prodigiosin
711945 8.00 0.03 7.08 8.00 Mol 0.20 -0.87 Acetamide, N,N'-[1,5-dioxo-1,5-pentanediyldi[1-(chloromethyl)- 2,3-dihydro-5-hydroxy-1H-benz[e]indole-3,7-diyl]]bis-
751249 7.98 0.02 7.15 8.00 Mol -0.76 -1.45 BEZ235 Clinical trial STK
645807 7.95 0.05 7.00 8.87 Mol -0.25 -0.67 ANTINEOPLASTIC-645807 Unknown
118028 7.88 0.03 6.95 8.00 Mol -0.21 1.29 Phenazastanine, 5,10-dihydro-5,10,10-trimethyl-
628585 7.78 0.02 7.29 8.00 Mol -0.36 1.62 ANTINEOPLASTIC-628585
674699 7.77 0.05 6.04 8.00 Mol -0.26 -0.94 9-[3-[N-(2-N,N-Dimethylamino)ethyl]aminopropyl]amino- 1-nitroacridine.3HCl Unknown
33669 7.69 0.04 6.49 8.46 Mol -0.35 -0.91 Emetine Hydrochloride Unknown
76712 7.67 0.02 7.26 8.00 Mol 0.28 -0.59 Anisomycin Unknown
668360 7.67 0.05 6.43 8.00 Mol -0.47 -0.63 Ethanone, 1,1'-[(1,1'-biphenyl)-2,2'-diyl] bis[2-(triphenylphosphoranylidene)- Unknown
32944 7.64 0.03 6.40 8.03 Mol -0.23 -0.89 Emetan-6'-ol, 7',10,11-trimethoxy-, dihydrochloride (9CI) Unknown
60387 7.64 0.04 6.91 8.00 Mol -0.18 -0.58 Dibenzo[f,h]pyrrolo[1,2-b]isoquinoline, 9,11,12,13,13a,14-hexahydro-2,3,5,6-tetramethoxy-, (R)- (9CI) Unknown
76557 7.64 0.03 7.00 8.00 Mol -0.39 1.81 Tin, bis(triphenyl- ) ethylenebis(dithiocarbamate)
743135 7.60 0.04 6.42 8.00 Mol -0.74 -1.59 (11aS)-7-methoxy-8-(5-[4-(4-quinazolinyl)piperazino]pentyloxy)-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
743121 7.58 0.04 6.43 7.98 Mol -0.69 -1.62 (11aS)-7-methoxy-8-3-[4-(4-quinazolinyl)piperazino]propoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepine-5-one
43675 7.57 0.04 6.56 7.91 Mol -0.37 5.27 Brestanol
673793 7.56 0.05 6.16 8.00 Mol -0.17 -0.83 9-Acridinamine, N-[2-[bis(2-hydroxyethyl)amino]ethyl]-7-methoxy-1-nitro- Unknown
716802 7.55 0.02 6.84 8.00 Mol -0.01 -0.71 Dibenzo[f,h]pyrrolo[1,2-b]isoquinolin-14-ol, 9,11,12,13,13a,14-hexahydro-2,3,6,7-tetramethoxy-, (13aS-trans)-
744327 7.54 0.04 6.41 8.00 Mol -0.76 -1.62 7-methoxy-8-[(5-2-methoxy-4-[(E)-3-(2,4-dimethyl-3-quinolyl)-3-oxo-1-propenyl]phenoxypentyl)oxy]-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
168597 7.52 0.04 6.89 8.37 Mol -0.40 5.28 Plumbane, chlorotributyl- Unknown
129414 7.51 0.04 6.50 8.00 Mol -0.23 -0.98 (.+-.)-2,3-Dehydroemetine dihydrochloride
624548 7.47 0.03 7.00 8.10 Mol 0.07 -1.24 Benzamide, N-[[[4-[(5-bromo-2-pyrimidinyl)oxy]-3- chlorophenyl]amino]carbonyl]-2-nitro-
145669 7.44 0.05 6.34 8.00 Mol -0.45 -0.74 4(1H)-Quinazolinone, 2,3-dihydro-2-(1-naphthalenyl)- (9CI) Unknown
76387 7.44 0.05 6.42 8.31 Mol -0.21 -0.57 Dibenzo[f,h]pyrrolo[1,2-b]isoquinoline, 9,11,12,13,13a,14-hexahydro-2,3,6,7-tetramethoxy-, (S)- (9CI)
744023 7.38 0.05 6.46 7.73 Mol -0.51 -1.25 (11aS)-8-(3-{4-[(E)-3-(2-hydroxyphenyl)-3-oxo-1-propenyl]-2-methoxyphenoxy}propoxy)-7-methoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
41390 7.36 0.03 6.80 7.77 Mol -0.05 -0.86 ANTINEOPLASTIC-41390
649890 7.35 0.03 6.51 7.74 Mol 0.34 -0.67 Alvocidib Hydrochloride Clinical trial STK
185 7.33 0.04 6.66 7.75 Mol 0.19 0.61 .beta.-[2-(3,5-Dimethyl-2-oxocyclohexyl)-2-hydroxyethyl]glutarimide Unknown
92904 7.31 0.03 6.80 7.84 Mol -0.02 -0.66 ANTINEOPLASTIC-92904
100055 7.26 0.04 6.31 8.00 Mol -0.04 -0.79 Tylophorinine Unknown
263434 7.14 0.05 6.23 7.74 Mol -0.20 -0.82 N,N'-Bis(3-methoxy-9-acridinyl)-1,8-octanediamine
750213 7.04 0.05 5.82 7.55 Mol -0.08 -0.66 4-(2-hydroxyethyl)-10-phenyl-3,4,6,7,8,10-hexahydro-1H-cyclopenta[g]furo[3,4-b]quinolin-1-one
22323 6.92 0.03 6.57 7.77 Mol -0.40 5.28 Chlorid tri-N-butylcinicity (CZECH)
742296 6.91 0.05 6.03 7.88 Mol -0.64 -1.44 (11aS)-8-(5-[4-(1,3-benzothiazol-2-yl)-2-methoxyphenoxy]pentyloxy)-7-methoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
102980 6.86 0.02 6.66 7.25 Mol -0.39 2.45 (2,4-Dichlorophenoxy)tributylstannane
706126 6.84 0.03 6.36 7.38 Mol 0.14 -0.64 (2R,3S,4S)-3,4-O-Diacetyl-3,4-dihydroxy-2-(p-methoxybenzyl)-pyrrolidine hydrochloride
751342 6.80 0.04 6.17 7.50 Mol -0.33 -1.25 12H-Benzo[g]pyrido[2,1-b]quinazoline-4-carboxamide, N-[2(dimethylamino)ethyl]-12-oxo
695589 6.75 0.05 5.74 7.79 Mol 0.20 -1.13 6-Amino-3-chlormethyl-1-[(5-methoxyindol-2-yl)-carbonyl] indoline
674350 6.74 0.04 6.00 7.69 Mol -0.39 -0.52 3,6-Dimethylthio-dihydrotetrazine
146109 6.74 0.04 6.05 7.71 Mol -0.20 -0.65 Pseudourea, 2-[(10-methyl-9-anthryl)methyl]-2-thio-, monohydrochloride
141819 6.73 0.02 6.30 7.04 Mol -0.22 2.70 Bromotriphenyllead(IV)
306365 6.71 0.04 5.73 7.43 Mol -0.28 -0.76 Quino[8,7-h]quinoline-1,7-diamine, N,N'-bis[3-(dimethylamino)propyl]-3,9-dimethyl-, tetrahydrochloride
15013 6.68 0.05 5.74 7.16 Mol -0.11 -0.36 ANQI
178264 6.68 0.05 5.67 7.36 Mol -0.19 -0.06 Fluopsin N Unknown
220589 6.68 0.04 5.94 7.45 Mol -0.55 -0.73 Ethanol, 2,2'-[[2-(5-nitro-2-furanyl)-4-quinazolinyl]imino]bis- (9CI)
679748 6.66 0.05 5.72 7.70 Mol 0.17 -0.26 [1,1'-Binaphthalene]-3,3',4,4'-tetrone, 2,2',6,6'-tetramethyl- Unknown
745357 6.66 0.04 5.76 6.77 Mol -0.14 -0.61 Bispurines
633555 6.63 0.04 6.00 7.00 Mol 0.11 -0.34 Acylfulvene
740383 6.63 0.05 5.78 7.24 Mol -0.47 -0.95 3,7-di(trifluoromethyl)-2-(thien-2-ylcarbonyl)quioxaline 1,4-dioxide
743122 6.62 0.03 5.77 7.24 Mol -1.08 -1.74 N1-[4-chloro-2-(2-chlorobenzyl)phenyl]-2-[4-(5-[-(11aS)-7-methoxy-5-oxo-2,3,5,11a,-tetrahydro-1H-benzo[e]pyrrolo[1,2-a] [1,4]diazepin-8-yl]oxybutyl)piperazino]acetamide
178296 6.61 0.04 5.67 7.23 Mol -0.32 -0.47 Atenase
47731 6.60 0.04 5.82 7.32 Mol -0.27 -0.40 Aniline, p-[[p-(dimethylamino)phenyl][4-(methylimino)-2,5-cyclohexadien-1-ylidene]methyl]-N,N-dimethyl-, monohydrochloride (8CI)
744332 6.59 0.03 5.71 6.86 Mol -0.64 -1.36 (11aS)-7-methoxy-8-6-[4-(2-methyl-4-oxo-3,4-dihydro-3-quinazolinyl)phenoxy]pentyloxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
743134 6.59 0.04 5.98 7.35 Mol -1.09 -1.75 N1-[4-chloro-2-(2-cholrobenzoyl)phenyl]-2-[4-(6-[(11aS)-7-methoxy-5-oxo-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-8-yl]oxyhexyl)piperazino]acetamide
674351 6.58 0.03 6.01 7.24 Mol 0.10 -0.41 1,4-Dimethoxy-7-bromo-5H-benzocycloheptene
742543 6.58 0.05 5.72 7.21 Mol -0.05 -0.72 Naphth[1',2':4,5]imidazo[1,2-a]pyridine-5,6-dione, 9-methyl-
744336 6.56 0.04 5.55 6.92 Mol -0.50 -1.57 (11aS)-7-methoxy-8-(4-2-methoxy-4-[5-(3,4,5-trimethoxyphenyl)-4,5-dihydro-3-isoxazolyl]phenoxybutoxy)-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
664215 6.54 0.05 5.92 7.40 Mol 0.38 0.05 Chloro-methoxy-tetrangulol Unknown
299863 6.52 0.02 6.15 7.07 Mol -0.14 -0.33 Benzenemethanol, 4-(1,1-dimethylethyl)-.alpha.,.alpha.-bis[4-(1,1-dimethylethyl)-2,6-dimethoxyphenyl]-2,6-dimethoxy-
349155 6.50 0.04 6.00 7.31 Mol 0.03 -0.47 B844009K069
205105 6.50 0.05 5.56 7.40 Mol -0.49 -0.72 Hydrazinecarbothioamide, 2-[(5-amino-1-isoquinolinyl)methylene]- (9CI)
265959 6.49 0.04 5.14 7.27 Mol -0.28 -0.71 6H-Cyclopenta[c][1,8]phenanthrolin-6-one, 5,7,8,9-tetrahydro-
702015 6.48 0.04 5.78 6.89 Mol -0.60 -1.47 1H-Indole-2-carboxylic acid, 2,3,5,11a-tetrahydro-7-methoxy-5-oxo- 1H-pyrrolo[2,1-c][1,4]benzodiazepin-8-yl ester, (11aS)-
5013 6.48 0.03 5.82 6.77 Mol -0.17 -0.52 C.I. Solvent Blue 3
745355 6.45 0.04 5.79 7.16 Mol -0.53 -1.42 7-methoxy-8-(4-2-methoxy-4-[(10-oxo-9,10-dihydro-9-nthracenyliden)methyl]
37187 6.45 0.04 5.47 6.97 Mol -0.31 -0.52 Acco Naf-Sol AS-KB
103837 6.42 0.03 5.72 6.71 Mol -0.42 0.48 .beta.-Resorcylaldehyde, 1,4-phthalazinediyldihydrazone
370589 6.42 0.04 5.55 6.65 Mol -0.56 -1.40 2-Pyridinecarbaldehyde (5-methyl-5H-[1,2,4]triazino[5,6-b]indol-3-yl)hydrazone
671196 6.41 0.03 6.08 7.22 Mol 0.29 -0.22 Elsinochrome B Unknown
37608 6.41 0.04 5.45 6.76 Mol -0.20 -0.49 C.I. Azoic Coupling Component 27
744989 6.40 0.05 5.52 6.73 Mol -0.72 -1.61 7-methoxy-8-[(5-2-methoxy-4-[(E)-3-(2,4-dimethyl-3-quinolyl)-3-oxo-1-propenyl]phenoxybutyl)oxy]-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
751286 6.40 0.03 5.29 6.61 Mol -0.55 -1.46 5-Methyl-3-(2-(pyridin-2ylmethyl)hydrazinyl)-5H-[1,2,4]triazino[5,6-b]indole, trihydrochloride
242557 6.40 0.04 5.90 7.19 Mol -0.25 -0.24 (3,5-Di-t-butyl-4-hydroxybenzylidene)malononitrile
33409 6.38 0.04 5.59 6.75 Mol -0.29 -0.56 Colchinol, N-acetyliodo-, methyl ether
335307 6.38 0.04 5.48 6.89 Mol -0.38 -0.08 Carbamic acid, [5-(cyclopropylcarbonyl)-1H-benzimidazol-2-yl]-, methyl ester (9CI)
1010 6.37 0.03 5.75 6.63 Mol -0.43 -1.10 7-[.ALPHA.-(P-NITROANILINO)BENZYL]-8-QUINOLINOL
68088 6.37 0.04 5.43 6.74 Mol -0.60 -1.00 Guanidine, [(p-fluoro-.alpha.-phenylbenzylidene)amino]-, monohydrochloride
527347 6.35 0.03 5.63 6.59 Mol -0.62 -0.56 Picolinaldehyde, 2-quinolylhydrazone (8CI)
3905 6.35 0.04 5.15 6.79 Mol -0.12 -0.37 .alpha.,.alpha.',.alpha.''-Tripyridyl
69603 6.35 0.04 5.58 7.28 Mol -0.27 -0.87 Quinoline, 4-(2,5-dimethoxystyryl)-
143103 6.35 0.05 5.44 7.21 Mol -0.40 -1.13 Methanesulfonamide, N-[4-[(3-methoxy-9-acridinyl)amino]phenyl]-, monohydrochloride (9CI) (MF1)
165714 6.29 0.04 5.69 7.42 Mol -0.20 -0.62 9-Acridinamine, N-(4-ethoxyphenyl)-, monohydrochloride
12454 6.27 0.04 5.60 6.63 Mol -0.07 -0.47 C.I. Basic Yellow 7
749673 6.25 0.05 5.37 7.17 Mol -0.71 -1.29 N1-(2,15-dioxo-1-(pyren-1-yl)-6,9,12-trioxa-3,16-diazanonadecan-19-yl)-N1-methyl-N3-(2-(naphthalen-2-yl)quinolin-4-yl)propane-1,3-diaminium bromide
83459 6.25 0.05 5.20 6.59 Mol -0.56 -0.87 Indole-2,3-dione, 3-(4,4-dimethyl-3-thiosemicarbazone)
33461 6.23 0.04 5.68 6.71 Mol -0.15 -0.46 Aniline, 4,4'-imidocarbonylbis[N,N-diethyl-, monohydrochloride (8CI)
13006 6.22 0.04 5.30 6.67 Mol -0.09 -0.86 Ethanol, 2-[(2-[(2-methoxy-9-acridinyl)amino]ethyl)amino]-, dihydrochloride
11515 6.15 0.04 5.75 6.51 Mol -0.29 -0.88 Acranil
678913 6.13 0.04 5.52 6.84 Mol -0.28 -0.81 4-Acridinecarboxamide, 1-chloro-N-[2-(dimethylamino) ethyl]-, dihydrochloride Unknown
674104 6.13 0.04 5.57 6.64 Mol -0.68 -1.20 2-Acetylimidazo[4,5-b]pyridin 4 p-nitrophenyl 3 thio-semicarbazone
71795 6.11 0.04 5.63 6.86 Mol 0.28 -0.71 Ellipticine
708472 6.11 0.03 5.63 6.51 Mol 0.63 -0.86 Beauvericin (8CI, 9CI)
742293 6.10 0.05 5.55 7.11 Mol -0.65 -1.47 (11aS)-8-4-[4-(1,3-benzothiazol-2-yl)phenoxy]butoxy-7-methoxy-2,3,5,11a-tetrahydro-1H-benzo[e]pyrrolo[1,2-a][1,4]diazepin-5-one
671197 6.09 0.03 5.61 6.62 Mol 0.34 -0.34 Elsinochrome C Unknown
741425 6.05 0.05 5.47 6.76 Mol -0.36 -0.76 3,7-di(trifluoromethyl)-2-naftoylquioxaline 1,4-dioxide
617969 6.05 0.04 5.32 6.65 Mol -0.21 -0.95 1,4-Acridinedicarboxamide, N,N'-bis[2-(dimethylamino) ethyl]-, trihydrochloride Unknown
740043 6.04 0.04 5.43 6.57 Mol -0.71 -1.37 7-bromo-indirubin with water-solubilizing extension on position 3'
5283 6.00 0.05 5.48 6.73 Mol -0.39 5.89 Chlorotriethylstannane
13002 5.99 0.03 5.76 6.53 Mol -0.13 -0.56 Acridine, 9-(p-dimethylaminoanilino)-
674067 5.85 0.05 5.70 6.75 Mol -0.55 -1.22 Bicyclo[2.2.1]heptan-2-amine, N,N'-(1,3-phenylene)bis[3-(5-methoxy-1H-indol-3-yl)-, stereoisomer Unknown

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